A 12-Nm 0.62-1.61 Mw Ultra-Low Power Digital CIM-based Deep-Learning System for End-to-End Always-on Vision.

En-Jui Chang,Cheng-Xin Xue,Chetan Deshpande,Gajanan Jedhe,Jenwei Liang,Chih-Chung Cheng,Hung-Wei Lin,Chia-Da Lee,Sushil Kumar,Kim Soon Jway,Zijie Guo,Ritesh Garg,Allen-Cl Lu,Chien-Hung Lin, Meng-Han Hsieh,Tsung-Yao Lin,Chih-Cheng Chen

2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)（2023）

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Key words

2-15 fps,compute RC loading,DCIM power,DCIM-DLS,DCIM-friendly dataflow strategy,end-to-end AoV,mW ultra-low power digital CIM-based,power 0.62 mW to 1.61 mW,power consumption,pushed-rule 2p8T SRAM bitcell,reconfigurable DCIM control scheme,ultra-low power DCIM-based

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